technologies and applications for green growth

SMART SENSOR NETWORKS: TECHNOLOGIES AND APPLICATIONS FOR GREEN GROWTH Summary Sensors and sensor networks have an important impact in meeting environmental challenges.. Various example

Smart Sensor Networks:

Technologies and Applications for

Green Growth

December 2009

ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT

The OECD is a unique forum where the governments of 30 democracies work together to address the economic, social and environmental challenges of globalisation The OECD is also at the forefront of efforts to understand and to help governments respond to new developments and concerns, such as corporate governance, the information economy and the challenges of an ageing population The Organisation provides a setting where governments can compare policy experiences, seek answers to common problems, identify good practice and work to co-ordinate domestic and international policies

The OECD member countries are: Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States The Commission of the European Communities takes part in the work of the OECD

FOREWORD

This report was presented to the Working Party on the Information Economy (WPIE) in June 2009 and declassified by the Committee for Information, Computer and Communications Policy in October

2009

The report has been prepared by Verena Weber, consultant, in conjunction with the OECD Secretariat

as part of the WPIE’s work on ICTs and the environment, under the overall direction of Graham Vickery, OECD Secretariat It contributed to the OECD Conference on “ICTs, the environment and climate change”, Helsingør, Denmark, 27-28 May 2009, and is a contribution to the OECD work on Green Growth For more information see www.oecd.org/sti/ict/green-ict This report was also released under the OECD code DSTI/ICCP/IE(2009)4/FINAL

OECD©2009

TABLE OF CONTENTS

SMART SENSOR NETWORKS: TECHNOLOGIES AND APPLICATIONS FOR GREEN GROWTH 6

Summary 6

Sensor technology for green growth 7

Sensors, actuators and sensor networks – a technology overview 7

Fields of application of wireless sensor networks 9

Selected applications and their environmental impact 10

Smart grids and energy control systems 10

Introduction, definition and main components 10

New and advanced grid components 13

Smart devices and smart metering 13

Programmes for decision support and human interfaces 18

Advanced control systems 18

The environmental impact of smart grids 18

Smart buildings 24

Introduction, definition and main components 24

The environmental impact of smart buildings 26

Transport and logistics 29

Introduction and overview of applications 29

The environmental impact of smart transportation 31

Industrial applications 35

Introduction and application examples 35

An example of the environmental impact of smart industrial applications 36

Precision agriculture and animal tracking 37

The environmental impact of precision agriculture and animal tracking 39

Conclusion 40

NOTES 41

REFERENCES 43

ANNEX A1 OTHER FIELDS OF SENSOR AND SENSOR NETWORK APPLICATIONS 47

Index of Tables and Figures

Table 1: Examples of sensor types and their outputs 8

Table 2: Selected smart grid definitions 12

Table 3: Strengths and weaknesses of different WAN technologies 16

Table 4: Overview of IEEE standards 17

Table 5: Comparison of the GeSI, EPRI and IPTS studies 19

Table 6: Impacts of ICTs in smart grids for different scenarios 23

Table 7: Cross-tabulated smart building applications and sensors 26

Table 8: Assumptions underlying the calculations of positive impacts 28

Table 9: Impacts of ICTs in facility management for different scenarios 29

Table 10: Assumptions underlying the calculations of positive impacts 32

Table 11: Impacts of Intelligent Transportation Systems (ITS) for different scenarios 34

Table 12: Assumptions underlying the calculations of positive impacts 37

Figure 1: Typical wireless sensor and actuator network 9

Figure 2: Architecture of a sensor node 9

Figure 3: Fields of application of wireless sensor networks 10

Figure 4: Main components of a smart grid 13

Figure 5: Smart meter 14

Figure 6: Overview of smart grid communication applications and technologies 15

Figure 7: Positive environmental impact of smart grids 21

Figure 8: Positive environmental impact of smart grids 22

Figure 9: Positive environmental impact of smart buildings 27

Figure 10: Overview of ITS applications and examples 30

Figure 11: Positive environmental impact of smart logistics 32

Figure 12: Positive environmental impact of smart motors 36

SMART SENSOR NETWORKS: TECHNOLOGIES AND APPLICATIONS FOR GREEN

GROWTH

Summary

Sensors and sensor networks have an important impact in meeting environmental challenges Sensor applications in multiple fields such as smart power grids, smart buildings and smart industrial process control significantly contribute to more efficient use of resources and thus a reduction of greenhouse gas emissions and other sources of pollution

This report gives an overview of sensor technology and fields of application of sensors and sensor networks It discusses in detail selected fields of application that have high potential to reduce greenhouse gas emissions and reviews studies quantifying the environmental impact

The review of the studies assessing the impact of sensor technology in reducing greenhouse gas emissions reveals that the technology has a high potential to contribute to a reduction of emissions across various fields of application Whereas studies clearly estimate an overall strong positive effect in smart grids, smart buildings, smart industrial applications as well as precision agriculture and farming, results for the field of smart transportation are mixed due to rebound effects In particular intelligent transport systems render transport more efficient, faster and cheaper As a consequence, demand for transportation and thus the consumption of resources both increase which can lead to an overall negative effect

This illustrates the crucial role governments have to enhance positive environmental effects Increased efficiency should be paralleled with demand-side management to internalise environmental costs Further, minimum standards in the fields of smart buildings and smart grids in regard to energy efficiency can significantly reduce electricity consumption and greenhouse gas emissions Finally, this report also highlights that applications of sensor technology are still at an early stage of development Government programmes demonstrating and promoting the use of sensor technology as well as the development of open standards could contribute to fully tap the potential of the technology to mitigate climate change

Sensor technology for green growth

Environmental degradation and global warming are among the major global challenges facing us These challenges include improving the efficient use of energy as well as climate change ICTs and the Internet play a vital role in both, being part of the problem (they consume energy and are a source of pollution) and have the potential to provide important solutions to it (ICT applications in other sectors have major potential to improve environmental performance)

Various examples illustrate the role of ICTs as a provider of solutions to environmental challenges:

Smart grids and smart power systems in the energy sector can have major impacts on improving energy distribution and optimising energy usage (Adam and Wintersteller, 2008) Smart housing can contribute to major reductions of energy use in hundreds of millions of buildings Smart transportation systems are a

powerful way of organising traffic more efficiently and reducing CO2 emissions

All these applications have one important attribute in common: They all rely on sensor technology and often on sensor networks Because of the important impact of applications of sensors and sensor networks in meeting environmental challenges, this analysis has been developed in the context of OECD’s work on ICTs and environmental challenges [see also DSTI/ICCP/IE(2008)3/FINAL and DSTI/ICCP/IE(2008)4/FINAL, and DSTI/ICCP/CISP(2009)2/FINAL for broadband investments in smart

grids] and the WPIE’s Programme of Work 2009–2010 It is also a direct follow-up to the Seoul Declaration for the Future of the Internet Economy, issued at the close of the OECD Ministerial Meeting

in June 2008, which invited the OECD and stakeholders to explore the role of information and communication technologies (ICTs) and the Internet in addressing environmental challenges

The report opens with some technological fundamentals in describing sensor technology and sensor networks This is followed by an overview of different fields of application Selected sensor and sensor network applications are discussed as well as their environmental impact

Sensors, actuators and sensor networks – a technology overview

Sensors measure multiple physical properties and include electronic sensors, biosensors, and chemical sensors This paper deals mainly with sensor devices which convert a signal detected by these devices into

an electrical signal, although other kinds of sensors exist These sensors can thus be regarded as “the interface between the physical world and the world of electrical devices, such as computers” (Wilson,

2008) The counterpart is represented by actuators that function the other way round, i.e whose tasks consist in converting the electrical signal into a physical phenomenon (e.g displays for quantities measures

by sensors (e.g speedometers, temperature reading for thermostats)

Table 1 provides examples of the main sensor types and their outputs Further sensors include chemical sensors and biosensors but these are not dealt with in this report Outputs are mainly voltages, resistance changes or currents Table 1 shows that sensors which measure different properties can have the same form of electrical output (Wilson, 2008)

Table 1: Examples of sensor types and their outputs

Position Linear Variable Differential Transformers (LVDT) AC Voltage

Source: OECD based on Wilson, 2008

Wireless sensor and actuator networks (WSANs) are networks of nodes that sense and potentially also

control their environment They communicate the information through wireless links “enabling interaction

between people or computers and the surrounding environment” (Verdone et al., 2008) The data gathered

by the different nodes is sent to a sink which either uses the data locally, through for example actuators, or

which “is connected to other networks (e.g the Internet) through a gateway (Verdone et al., 2008)

Figure 1 illustrates a typical WSAN1

Sensor nodes are the simplest devices in the network As their number is usually larger than the number of actuators or sinks, they have to be cheap The other devices are more complex because of the

functionalities they have to provide (Verdone et al., 2008)

A sensor node typically consists of five main parts: one or more sensors gather data from the environment The central unit in the form of a microprocessor manages the tasks A transceiver (included

in the communication module in Figure 2) communicates with the environment and a memory is used to store temporary data or data generated during processing The battery supplies all parts with energy (see Figure 2) To assure a sufficiently long network lifetime, energy efficiency in all parts of the network is

crucial Due to this need, data processing tasks are often spread over the network, i.e nodes co-operate in transmitting data to the sinks (Verdone et al., 2008) Although most sensors have a traditional battery there

is some early stage research on the production of sensors without batteries, using similar technologies to passive RFID chips without batteries

Figure 1: Typical wireless sensor and actuator network

Sink

Actuator

Node

Gateway Other Networkse.g Internet

Source: OECD based on Verdone et al., 2008

Figure 2: Architecture of a sensor node

Queries Data

Source: OECD based on Verdone et al., 2008

Fields of application of wireless sensor networks

There are numerous different fields of application of sensor networks For example, forest fires can be detected by sensor networks so that they can be fought at an early stage Sensor networks can be used to monitor the structural integrity of civil structures by localising damage for example in bridges Further,

they are used in the health care sector to monitor human physiological data (Verdone et al., 2008) The

following sections outline selected applications of wireless sensor networks

Figure 3: Fields of application of wireless sensor networks

precision agriculture and animal tracking

security and surveillance

industrial applications

health care (health monitoring, medical diagnostics)

environmental monitoring

entertainment

transportation and logistics

smart grids and energy control systems

urban terrain tracking and civil structure monitoring

smart buildings (e.g

indoor climate control)

applications of wireless sensor networks

Source: OECD based on Culler et al., Heppner, 2007, 2004, Verdone, 2008

Figure 3 shows the most important fields of application The upper part of Figure 3 shows fields of application discussed in more detail in this study as they have a high potential to tackle environmental challenges and reduce CO2 emissions The fields of application in the lower part of the figure are briefly discussed in Appendix A1 to give an overview of further interesting fields of application

Selected applications and their environmental impact

Smart grids and energy control systems

Introduction, definition and main components

Coal power plants are responsible for “nearly 40% of electricity production worldwide”, and electricity generation is thus responsible for a significant share of CO2 emissions (Atkinson, Castro, 2008)

To decrease emissions from the energy supply side, alternative clean technologies can be used to generate electricity or energy can be distributed in a more efficient way In both cases, sensor networks contribute to better and more efficient processes

On the generation side, sensor networks enable solar energy to be generated more efficiently Standalone panels “do not always capture the sun’s power in the most efficient manner” (Atkinson, Castro, 2008) Automated panels managed by sensors track sun rays to ensure that the sun’s power is gathered in a more efficient manner Such systems can also turn on and off automatically (Atkinson, Castro, 2008)

On the distribution side, energy is distributed in an often inefficient way in traditional grids At the time when present girds were planned and extended, they had one single mission, namely “to keep the lights on” (DOE, 2008) As a consequence, these grids have several shortcomings: many systems are centralised and rely on important central power stations making it difficult to integrate distributed energy resources and microgrids (EU, 2006) They most often only support one-way power flow and communication from the utility to consumers Further, utilities can barely track how energy is consumed across the grid (Atkinson and Castro, 2008) and, as a consequence, have no possibility to provide any pricing incentive to balance power consumption over time As utilities can only accommodate increases in demand up to a certain level, they are forced to rely on additional peak load power plants to cope with unexpected demand increases (Climate Group, 2008) This is highly expensive and potentially polluting, particularly if plants use fossil fuels (Atkinson and Castro, 2008)

As demand rises and additional power from distributed resources is fed into the grid, important

changes must be made The smart grid is an innovation that has the potential to revolutionise the

transmission, distribution and conservation of energy It employs digital technology to improve transparency and to increase reliability as well as efficiency ICTs and especially sensors and sensor networks play a major role in turning traditional grids into smart grids However, they are only one group

of key components of the smart grid The following section gives an extensive overview of the concept of the smart grid and its key components beyond a pure discussion of sensors and sensor networks as major benefits only arise from the interaction between these components

Defining the smart grid in a concise way is not an easy task as the concept is relatively new and as various alternative components build up a smart grid Some authors even argue that it is “too hard” to define the concept (Miller, 2008) Looking at different definitions reveals that the smart grid has been defined in different ways by different organisations and authors Table 2 gives an overview of selected definitions It shows two different approaches to define the smart grid: it is either defined from a solution perspective (“What are the main advantages of the grid?”) or from a components’ perspective (“Which components constitute the grid?”)

Table 2: Selected Smart Grid Definitions

Smart Grid A “smart grid” is a set of software and hardware tools that enable generators

to route power more efficiently, reducing the need for excess capacity and allowing two-way, real time information exchange with their customers for real time demand side management (DSM) It improves efficiency, energy monitoring and data capture across the power generation and T&D network

Adam and

Wintersteller

(2008)

Smart Grid A smart grid would employ digital technology to optimise energy usage,

better incorporate intermittent “green” sources of energy, and involve customers through smart metering

Miller (2008) Smart Grid The Smart Grid will:

Enable active participation by consumers Accommodate all generation and storage options Enable new products, services and markets Provide power quality for the digital economy Optimise asset utilisation and operate efficiently Anticipate and respond to system disturbances (self-heal) Operate resiliently against attack and natural disaster

Franz et al., (2006) eEnergy Convergence of the electricity system with ICT technologies

EPRI (2005) Intelli-Grid The IntelliGrid vision links electricity with communications and computer

control to create a highly automated, responsive and resilient power delivery system

DOE (2003) Grid 2030 Grid 2030 is a fully automated power delivery network that monitors and

controls every customer and node, ensuring a two-way flow of electricity and information between the power plant and the appliance, and all points in between Its distributed intelligence, coupled with broadband communications and automated control systems, enables real-time market transactions and seamless interfaces among people, buildings, industrial plants, generation facilities, and the electric networks

From a solution perspective, the smart grid is characterised by:

 More efficient energy routing and thus an optimised energy usage, a reduction of the need for excess capacity and increased power quality and security

 Better monitoring and control of energy and grid components

 Improved data capture and thus an improved outage management

 Two-way flow of electricity and real-time information allowing for the incorporation of green energy sources, demand-side management and real-time market transactions

 Highly automated, responsive and self-healing energy network with seamless interfaces between all parts of the grid

From a technical components’ perspective, the smart grid is a highly complex combination and integration of multiple digital and non-digital technologies and systems Figure 4 provides an overview of

the main component of a smart grid: i) new and advanced grid components, ii) smart devices and smart

metering, iii) integrated communication technologies, iv) programmes for decision support and human interfaces, v) advanced control systems These individual grids do not need to be centralised, but can have

more control stations and be more highly integrated The integration of many grids including spanning ones provides economic advantages, but there are challenges regarding security if they become too centralised and interconnected

country-Figure 4: Main components of a smart grid

new and advanced grid components

advanced control systems

smart devices and smart metering

programmes for decision support and human interfaces

integrated communication technologies

Overview ofsmart gridcomponents

Source: OECD based on SAIC, 2006, DOE, 2003, EPRI, 2006

New and advanced grid components

New and advanced grid components allow for a more efficient energy supply, better reliability and

availability of power Components include, for example, advanced conductors and superconductors, improved electric storage components, new materials, advanced power electronics as well as distributed energy generation Superconductors are used in multiple devices along the grid such as cables, storage devices, motors and transformers (DOE, 2003) The rise of new high-temperature superconductors allows transmission of large amounts of power over long distances at a lower power loss rate New kinds of batteries have greater storage capacity and can be employed to support voltage and transient stability (SAIC, 2006) Distributed energy is often generated close to the customer to be served which improves reliability, can reduce greenhouse gas emissions and at the same time expand efficient energy delivery (DOE, 2008) Furthermore, most of these alternative energy generation technologies close to customers

such as solar panels and wind power stations are renewable energy sources These technologies, e.g solar

panels, small hydro-electric and small hydro-thermals can be operated by consumers, or small providers

Smart devices and smart metering

Smart devices and smart metering include sensors and sensor networks Sensors are used at multiple places along the grid, e.g at transformers and substations or at customers’ homes (Shargal and Houseman,

2009b) They play an outstanding role in the area of remote monitoring and they enable demand-side management and thus new business processes such as real-time pricing

Spread over the grid, sensors and sensor networks monitor the functioning and the health of grid devices, monitor temperature, provide outage detection and detect power quality disturbances Control centres can thus immediately receive accurate information about the actual condition of the grid Consequently, maintenance staff can maintain the grid just-in-time in the case of disruptions rather than rely on interval-based inspections

Smart meters at customers’ homes play a crucial role They allow for real-time determination and information storage of energy consumption and provide “the possibility to read consumption both locally and remotely” (Siderius and Dijkstra, 2005) Further, they also provide the means to detect fluctuations and power outages, permit remote limitations on consumption by customers and permit the meters to be switched off This results in important cost savings and enables utilities to prevent electricity theft.2

Figure 5: Smart meter

Source: Siemens, 2008

Electricity providers get a better picture of customers’ energy consumption and obtain a precise understanding of energy consumption at different points in time As a consequence, utilities are able to establish demand-side management (DSM) and to develop new pricing mechanisms Energy can be priced according to real-time costs taking peak power loads into account and price signals can be transmitted to home controllers or customers’ devices which may then evaluate the information and power accordingly (DOE, 2003) Customers thus become more interactive with suppliers and “benefit from an increased visibility into their energy consumption habits” (IBM, 2007) They are aware of actual power costs rather than only obtaining a monthly or even yearly electricity bill To date, a number of OECD countries (Italy, Norway, Spain, Sweden and the Netherlands) have mandated the use of smart meters

Integrated communication technologies

Information provided by smart sensors and smart meters needs to be transmitted via a communication backbone This backbone is characterized by a high-speed and two-way flow of information Different communication applications and technologies form the communication backbone These can be classified into communication services groups (EPRI, 2006) Figure 6 provides an overview of these groups as well

as brief descriptions and examples

Figure 6: Overview of smart grid communication applications and technologies

 protocols needed to provide interoperable connectivity in a network that may vary greatly in topology and bandwidth

Core networking

Security Network management Data structuring and presentation Power system operations Consumer applications

An expanded view of different smart grid communication applications and technologies

 security measures for consumer portal communications as portals directly deal with consumer information and billing processes

 standard technologies for collecting statistics, alarms and status information on the communications network itself

 “meta-data” for formally describing and exchanging how devices are configured and how they report data

 several of the key applications for portals involve integration with distribution system operations, such as outage detection and power quality monitoring

 electrical metering and various aspects of building automation

e.g HTTP, TCP

e.g IPSec, HTTPS e.g Basic IP, SNMP e.g HTML, XML

 technology making a portal distinct from being just a “smart meter” or “smart thermostat” is its ability to network with other devices locally

e.g DSL, Cellular

e.g Ethernet, Wi-Fi

e.g DNP 3

e.g ANSI/IEEE C12

Source: OECD based on EPRI, 2006 and SAIC, 2006

Utilities have the choice between multiple and diverse technologies in the area of communication network technologies Usually, several network technologies are deployed within a smart grid The

following paragraphs provide an overview of different wide-area networks (WAN) and local-area networks (LAN) The distinction between WAN and LAN technologies is made in this context to differentiate between networks used to reach the customer and those at customer sites (EPRI, 2006)

Wide-area network technologies provide a means for a two-way information flow in the smart grid Multiple technologies are available which provide both broadband and narrowband solutions for the smart grid, resulting in a highly fragmented market Table 3 presents the main WAN technologies as well as their strengths and weaknesses for their deployment in the smart grid

The choice of WAN technologies will depend on factors such as reliability, low-cost, security and the network infrastructure that is already available It is likely that utilities will rely on several network technologies when they build smart grids as they have to cope with differences in geography, population densities as well as availability and competition of different network technologies in their services areas Some of these will require broadband, some will not

Table 3: Strengths and weaknesses of different WAN technologies

WAN technology Strengths Weaknesses

 decreasing bandwidth with distance

 high availability

 inconsistent bandwidth depending on number

of users and time of day

 relatively high costs

 no deployment in rural areas

WiMAX (IEEE 802.16)

 does not require deployment of a costly wired infrastructure

 early stage of deployment, uncertain whether the technology will meet its range targets

 cost of deployment3

 BPL not suited for particular applications as it

is dependent on current on the power line

 cost of deployment4

 not suited for particular applications as it is dependent on current on the power line

Cellular Services  high coverage area

 potentially low costs

 fast development of new technology (danger of being tied to one provider)

 some packet-switched services not very reliable

 high costs

 low effective bandwidth

 additional security measures required

 low reliability during bad weather conditions

 low costs

 reliability

 low bandwidth and thus only support of a few applications such as simple emergency alerts

Source: OECD adapted from EPRI, 2006

LAN technologies connect different smart devices at customers’ sites These technologies can be

classified into three main groups: wireless IEEE standards 802.x, wired Ethernet, as well as in-building power line communications (EPRI, 2006)

Wireless IEEE standards include Wi-Fi (IEEE 802.11), WiMAX5 (IEEE 802.16), ZigBee (IEEE 802.15.4) and Bluetooth (IEEE 802.15.1) Based on EPRI (2006), Table 4 shows how these standards can

be employed for different applications at customers’ sites and it provides a short description of strengths and weaknesses of these standards

Table 4: Overview of IEEE standards

IEEE standard Applications Strengths Weaknesses

Wi-Fi

(IEEE 802.11)

 connecting equipment at customer’ site

 access between WAN networks and customers’

 connection of sensors and other equipment in a customer LAN

 low power requirements

 low implementation cost

 good scalability (many devices can be connected)

 particularly designed for use in industrial and home automation or security applications

 connection of sensors and other equipment in a customer LAN

 more mature than ZigBee

 many products already available

 permits higher data rates than ZigBee

 so far, most equipment does not have Bluetooth implementation

 limited maximum number

of devices in a network

 security vulnerabilities

Source: Based on EPRI, 2006

Wired Ethernet is the prevalent LAN technology today Customers’ sites can be connected via

Ethernet with WAN or other networks Due to its wide use, it has important market support, multiple different products are available and costs are relatively low (EPRI, 2006) However, it is a local area network technology only

In-building power line communications: The two most common technologies in this area are Home

Plug and X10 (EPRI, 2006) Home Plug is a broadband over power line (BPL) system that provides a bit rate of approximately 14 Mbps (The Power Alliance, 2009b) It is suited for applications requiring Quality

of Service (QoS) with four different levels of priority Further, encryption mechanisms are available It can

be deployed to connect equipment at customers’ site Newer versions also support advanced portal applications such as entertainment delivery (EPRI, 2006) Strengths of the Home Plug network include connectivity to home wiring and QoS features (EPRI, 2006) The main shortcoming is the lack of standards both at the national and international level Currently, the Home Plug Alliance that promotes Home Plug works together with the ZigBee Alliance and EPRI define a Smart Energy Standard for consumer applications (The Home Plug Alliance, 2009a)

X10 “is the earliest, and probably the most popular, power-line carrier system for home automation”

and a “convenient mechanism for a portal to control load equipment (e.g thermostats, pool pumps)”

(EPRI, 2006) Strengths include the common use implying that multiple equipments are compatible with X10 and low implementation costs if devices already use power lines (EPRI, 2006) However, it cannot be

used as a general purpose LAN Further, it is a de facto standard only and there is no open access to the

protocol (EPRI, 2006)

Overall, defining a smart grid’s communication backbone at the early stage including different network technologies is paramount for the interoperability of different devices If not done properly at an

standards, adding greatly to time and expense” (Shargal and Houseman, 2009a) At this stage of development, a compilation of information regarding the success or failure of electricity service providers

in their choices for the communication backbone to their smart grid will be invaluable This will, for example, help telecommunications regulators to work out what kind of investment in national broadband infrastructures will help to achieve the aims of building smart infrastructures.6

Programmes for decision support and human interfaces

Another key component area of the smart grids comprises programmes for decision support and human interfaces The data volume in smart grids will increase tremendously compared to traditional grids

As Houseman and Shargal (2009) suggest, “a utility with five million customers […] will have more data from their distribution grid than Wal-Mart gets from all of its stores, and Wal-Mart manages the world’s largest data warehouse” One of the main challenges of utilities is thus on the one hand the integration and management of the generated data and on the other hand making the data available to grid operators and managers in a user-friendly manner to support their decisions

Tools and applications include systems based on artificial intelligence and semi-autonomous agent software, visualisation technologies, alerting tools, advanced control and performance review applications (SAIC, 2006) as well as data and simulation applications and geospatial information systems (GIS) Artificial intelligence methods as well as semi-autonomous agent software, for example, contribute to minimise data volume “and to create a format most effective for user comprehension” whereby the software has features that learn from input and adapts (SAIC, 2006) New methods of visualisation enable integration of data from different sources, providing information on the status of the grid and power quality and rapid information on instabilities and outages Finally, geographic information systems provide geographic, spatial and location information and tailor this information to the specific requirements for decision support systems along the smart grid

Advanced control systems

Advanced control systems constitute the last group of the smart grids’ key components They monitor and control essential elements of the smart grid Computer-based algorithms allow efficient data collection and analysis, provide solutions to human operators and are also able to act autonomously (SAIC, 2006) For example, new substation automation systems have been developed that provide local information and that can also be monitored remotely Whereas the substation information is only available locally in traditional smart grids, new developed subsystems are capable of making this information available in the whole grid and thus provide better power management Faults can be detected much faster than in traditional grids and outage times can be reduced

The environmental impact of smart grids

Studies which aim at quantifying the environmental impacts of smart grids typically only quantify positive impacts Currently there is a lack of data which quantifies the negative footprint of ICT infrastructure involved in smart grids In the following section three studies that examine the CO2e (CO2

equivalent)7 abatement potential of smart grids are discussed (see Table 5)

Table 5: Comparison of the GeSI, EPRI and IPTS studies

GeSI (2008) EPRI (2008) IPTS (2004)

Title Smart 2020: Enabling the Low

Carbon Economy in the Information Age

The Green Grid Energy Savings and Carbon Emissions Reductions Enabled

by a Smart Grid

The Future Impact of ICTs on Environmental Sustainability

 Reduced consumption through user information

 Demand side management

 Continuous commissioning for commercial buildings

 Reduced line losses

 Enhanced demand response and (peak) load control

 Direct feedback on energy usage

 Enhanced measurement and verification capabilities

 Facilitation of integration of renewable resources

 Facilitation of plug-in hybrid electric vehicle (PHEV) market penetration

 Renewable energy sources

Considered

impacts

 Positive impacts

 Negative footprint: no consideration on the smart grid level (overall ICT level)

 Positive impacts

 No consideration of negative footprints

 Positive impacts

 Negative impact considered but not on the smart grid level

Rebound

effects

 Only discussed in a qualitative way

 Only discussed in a qualitative way

 Quantification of the rebound effect

Methodology  Expert interviews

 Literature review: publicly available studies, academic literature

 Information provided by partner companies

 Case studies

 Quantitative analysis (models based on the McKinsey cost curve and McKinsey emission factors)

 Calculations draw on data from single cases

 Simple assumption are made to calculate impacts

 Screening and scoping

Scenario BAU (Business as usual) No concrete scenarios (only

ranges of savings are shown which depend on different market penetration rates)

Three scenarios:

 Technology

 Government First

 Stakeholder democracy

Table 6: Comparison of the GeSI, EPRI and IPTS studies (cont’d)

GeSI (2008) EPRI (2008) IPTS (2004)

Plausibility  Use of CO2e emission data

from IPCC (2007) with higher CO2e emission prospects than prospects provided by the IEA

 Possible overestimation of the positive impacts due to some assumptions

 Overall, use of good data

 Possible overestimation of some effects due to some assumptions

 Partially very simple assumptions and calculations

 Consideration of various

effects ( e.g rebound

effects)

 Most holistic approach

 Only report with validation

methods

Stakeholders  Involvement of industry

stakeholders

 Commissioned by GeSI (ICT industry association)

 EPRI: research institute of the power industry

 Research institutes, scientific report

 Involvement of scientific and industry stakeholders

Source: Erdmann, 2009

The GeSI study (2008) evaluates the opportunity of smart grids by both presenting a case study for India and by quantifying global positive impacts According to the study, power losses in India accounted for 32% of total power production in 2007 Currently, utilities are not able to detect where the losses occur

in the traditional grids ICT platforms with remote control systems, energy accounting and smart meters could have tremendous effects as they would allow utilities to track the sources of losses Further, India mainly relies on coal-based energy supply to meet increasing demand Decentralised energy generated by renewable energy sources could be integrated in a smart grid Smart grids would thus help to address two major needs of Indian energy providers: stemming losses and reducing carbon intensity

For the quantification of the positive impact, the study assesses four levers that have the potential to reduce CO2e emissions: i) reduced transmission and distribution (T&D) losses, ii) integration of renewable energy sources, iii) reduced consumption through user information, and iv) demand side management

(DSM) The study identifies total emission savings of 2.03 GtCO2e in 2020 in a “Business as Usual” (BAU)8 scenario Figure 7 shows the contribution of each lever as well as the assumptions behind the calculations Assumptions are based on expert interviews It should be noted that the GeSI estimates of the overall CO2e emissions for the year 2020 are based on the global CO2e emission data published by the IPCC (Intergovernmental Panel on Climate Change)9 which are higher than IEA estimates, for example

Whereas the GeSI Smart Grid study assesses the positive environmental impact on a global level in

2020, EPRI (2008) focuses on the positive environmental impacts on a national level in the United States for the year 2030 Another difference is the extended view on levers leading to a positive impact: overall,

the study evaluates seven levers: i) continuous commissioning for commercial buildings, ii) reduced line losses, iii) enhanced demand response and (peak) load control, iv) direct feedback on energy usage, v) enhanced measurement and verification capabilities, vi) facilitation of integration of renewable resources, and vii) facilitation of plug-in hybrid electric vehicle (PHEV) market penetration PHEV are “hybrid

electric vehicles that can be plugged into electrical outlets for recharging” (EPRI, 2008) As PHEV allow for CO2 emission savings,10 the study attributes 10-20% of these savings to the smart grid as the smart grids allow charging of vehicles over night However, R&D on PHEV is still at an early stage As the study evaluates CO2e emission savings for a longer time horizon than the GeSI study, the inclusion of PHEV can

be regarded as useful However, the percentage of emission savings from PHEV attributed to smart grids seems potentially overstated

Figure 7: Positive environmental impact of smart grids

0,02

2,03

0,89

0,28 0,83

Total CO 2 e

reduction

potential

Reduced trans- mission and distribution (T&D) losses 1)

Integration

of renewable energy sources 2)

Reduced consumption through user information 3)

Demand side management 4)

Assumptions:

1) 30% reduction (14% to 10%) of T&D losses for developed countries and 38% (24% to 15%) reduction for developing countries

2) 10% reduction in the carbon intensity of generation of developed countries

2) 5% reduction in the carbon intensity of generation of developing countries 3) 5% reduction in energy consumption

3) Effective in 75% of residential new builds and 50% of residential retrofits 3) Effective in 60% of commercial new builds and 50% of commercial retrofits

4) 3% (10 days a year) reduction in spinning reserve

CO 2 e reduction potential in GtCO 2 e

Note: taken from GeSI 2008

For each level, the study develops different market penetration ranges and thus obtains evaluations for low and high market penetration Overall, the EPRI study estimates CO2e energy saving ranging from 60-

211 million metric tons Figure 8 provides a detailed overview of CO2e savings which arise from the seven levers

Figure 8: Positive environmental impact of smart grids according to EPRI (2008)

60

5 211

68 16

Total CO 2

reduction

potential

sioning for commercial buildings

Commis-Reduced line losses

Demand response and (peak) load control

Direct feedback

on energy usage

Enhanced measure- ment and verification capabilities

facilitation

of gration of renewable resources

inte-Facilitation

of PHEV market penetration

Note: taken from GeSI 2008

Overall, the impact range is between the low-end value of 60 million tons and the high-end value of

211 million tons CO2e emission savings vary considerably This is due to different shares of market penetration Furthermore, estimations are partially based on simple assumptions as well as on data from single cases

The third study discussed in this section assesses both positive and negative impacts of ICTs on environmental sustainability (IPTS, 2004) As opposed to the above studies, it studies one important lever: the contribution of renewable energy sources to a reduction of CO2 emissions and especially the impact of ICTs on the share of renewable energy sources ICTs facilitate the integration of energy which was generated by renewable energy sources According to the authors, the use of ICTs in the smart grid increases the total share of renewable energy sources in the range of 2-7% in 2020 The range is due to best and worst-case values for three different scenarios as shown in Table 6 A total reduction in GHG emissions (measured in CO2e) due to the use of ICTs in energy supply ranges from 1.5% in the worst case and 3.1% in the best case

Table 7: Impacts of ICTs in smart grids for different scenarios

Scenario A Scenario B Scenario C

High level of competition

High awareness and interest

CO2e reductions in 2020 Rebound effects which arise from a higher efficiency in energy supply are included in the IPTS study, which is not the case for the GeSI and EPRI studies In terms of scenario building, validation measures and the integration of positive and negative effects, the IPTS study is the most sophisticated presented in this section It is also the only study which integrates rebound effects

Comparing actual CO2e emission values is a difficult task as the conception of these studies differs significantly They assess different smart grid levels on different continents for differing time horizons Overall, all studies emphasise that fully and properly deployed smart grids could have an important and strong potential to reduce future CO2e emissions The GeSI study, for example, which assesses the environmental impacts of several smart (sensor) applications, attributes the highest potential to smart grids

to reduce CO2e emissions

However, it may be also necessary to investigate the potential negative environmental impact associated with the deployment of smart grids, for example, the amounts of additional hardware needed to support and improve the electric transmission grid These new activities may also require new rights of way and distribution systems with possible negative impacts on wildlife and ecosystems

Because of the potential positive impacts of smart grids, many OECD countries have emphasised the transformation of actual grids into smart grids For example, the provisions of the U.S stimulus bill signed

in February 2009 include USD 11 billion for “smart grid” investments Furthermore, some OECD countries (Italy, Norway, Spain, Sweden and the Netherlands) have already issued mandates for smart metering, and the EU Communication on ICTs and the environment (13 March 2009) emphasises the role

of smart metering

One of the main questions for successful implementation of smart grids will be whether energy suppliers can agree on working together to adopt industry-wide solutions and developing and adopting open standards (Adam, Wintersteller, 2008)

Smart buildings

Introduction, definition and main components

Smart buildings are a field closely linked to smart grids Smart buildings rely on a set of technologies that enhance energy-efficiency and user comfort as well as the monitoring and safety of the buildings Technologies include new, efficient building materials as well as information and communication technologies (ICTs) An example of newly integrated materials is a second façade for glass sky scrapers The headquarters of the New York Times Company has advanced ICT applications as well as a ceramic sunscreen consisting of ceramic tubes which reflect daylight and thus prevent the skyscraper from collecting heat (see Box 1)

ICTs are used in: i) building management systems which monitor heating, lighting and ventilation, ii)

software packages which automatically switch off devices such as computers and monitors when offices

are empty (SMART, 2020) and iii) security and access systems These ICT systems can be both found at household and office level Furthermore, according to Sharpels et al., (1999), first-, second- and third-

generation smart building systems can be distinguished.11 First-generation smart buildings are composed of many stand-alone self-regulating devices which operate independently from each other Examples include security and HVAC systems In second-generation smart buildings, systems are connected via specialised networks which allow them to be controlled remotely and “to facilitate some central scheduling or

sequencing” (Sharpels et al., 1999), e.g switching off systems when rooms and offices are not occupied

Third-generation smart building systems are capable of learning from the building and adapting their monitoring and controlling functions This last generation is at an early stage

Sensors and sensor networks are used in multiple smart building applications These include:

 Heating, ventilation, and air conditioning systems (HVAC)

 Lightning

 Shading

 Air quality and window control

 Systems switching off devices

 Metering (covered in the section on smart grids)

 Standard household applications (e.g televisions, washing machines)

 Security and safety (access control)